Quantitative histomorphometry is the current gold standard for objective measurement of
nerve architecture and its components. Many methods still in use rely heavily upon manual …

Abstract Background/Objectives: The primary objective of this paper is to classify the clinical
dataset of cervical cancer to identify the stage of cancer which helps in proper treatment of …

Cervical cancer is the second most common and the fifth deadliest cancer in women. In this
paper, we propose a deep learning approach for detecting cervix cancer from pap-smear …

This paper presents a method of overlapping/aggregating nuclei cells segmentation. This
method is based on the watershed segmentation algorithm, but the specificity of this work is …

After binarization of cells in complex cytological and histological images the segmented
structures can be rather far away from a final quantification of features of single cells since …

Extraction of cell nuclei from hematoxylin and eosin (H&E)-stained histopathological images
is an essential preprocessing step in computerized image analysis for disease detection …

The segmentation of structures of complex cytological and histological images is a
necessary intermediate step for image analysis that give rise to binary images. In many …

In this work, an image analysis approach for automated detection, segmentation, and
classification of particular cells, specially the cancer cells from normal cells is introduced. In …

This paper presents a new segmentation method of complex nucleus configurations. The
specificity of this work is to introduce prior information about the usual shape of cells nuclei …

Clustering is the process of discovering groups within the data, based on similarities, with a
minimal, if any, knowledge of their structure. The self-organizing (or Kohonen) map (SOM) is …